Social network graph inference and aggregation with portability, protected shared content, and application programs spanning multiple social networks

ABSTRACT

An application program spans a plurality of digital social networks. The application program includes an inferred digital social network. Consent is obtained from a plurality of users of the digital social networks to participation in the inferred digital social network. Information is automatically obtained from the digital social networks for the users, through a plurality of respective communication channels, which can be application program interfaces or covert or subliminal channels. The information includes link information between each of the users and other individuals in the digital social networks. The information is aggregated for the users to form the inferred digital social network, corresponding to a graph having nodes representing the users and the other individuals and having links between the nodes representing social relationships. Each of the users is enabled to send and receive message information with other users, to view profile information of other users, and to view social contact information of other users, through the inferred digital social network. In response to inputs from the users, the application program provides state information to the digital social networks spanned by the application program that the digital social networks cause to be communicated to users of the digital social networks.

CROSS-REFERENCE TO RELATED APPLICATION

This patent application claims the benefit of F. David Serena,Provisional Application No. 61/511,983, filed Jul. 26, 2011, which ishereby incorporated herein in its entirety.

TECHNICAL FIELD

The field of the invention generally relates to computer-based socialnetworks, and more particularly to social networks inferred frompre-existing traditional social networks, and application programs thatspan multiple pre-existing traditional social networks.

BACKGROUND

Computer-based social networks such as FACEBOOK, GOOGLE+, PING, orLINKEDIN provide opportunities for individuals to maintain, nurture, anddevelop relationships with friends or business contacts. These networkstypically enable their participants to view profiles of otherparticipants, and to link with other participants with whom apre-existing actual relationship exists or with whom an actual social orbusiness relationship is desired. Typically, once linked togetherthrough a computer-based social network, participants can exchangecommunications, photographs, or other media content, and can view theidentities of persons with whom the other participant has relationshipsthrough the social relationship network.

Social networks can be represented by a graph structure wherein nodesare individuals or other entities and links (potentially weighted)represent connections between the parties. It has been assumed in modernlarge social networks such as FACEBOOK, GOOGLE+, PING and LINKEDIN thatthe network itself is owned by the major providers. Many of the rights,however, are owned by the constituent members of the social network(some of these ownership rights of the user are actually specified in“terms of service”).

Graph inference is a technology that determines graph content throughobservations and logical inference. The technology is to determineoverall graph structure from partial information. Social networkscontain more state information (such as photos, multimedia, games,privacy information, blocking of individuals) than the standarddefinition of a social graph, and edge weightings of the graph may beimplied to designate link quality information, as is detailed in Serena,“Relationship Networks Having Link Quality Metrics with inference andConcomitant Digital Value Exchange,” U.S. patent application Ser. No.13/177,856, filed Jul. 7, 2011, which is hereby incorporated herein byreference. Furthermore, individuals have a view of the world via socialnetworks that does not contain all links but contains a view ofconnectedness, including degrees of separation to neighbors in the graphstructure (for example, suggested friends lists can be used as a basisfor garnering information about the social graph).

SUMMARY

In one general aspect, the invention provides a method of operating aninferred digital social network. Consent is obtained from a plurality ofusers of at least one digital social network to participation in theinferred digital social network. Information is automatically obtainedfrom the digital social network for the plurality of users of thedigital social network. The information includes link informationbetween each of the plurality of users and other individuals in thedigital social network. The information is aggregated for the pluralityof users to form the inferred digital social network, corresponding to agraph having nodes representing the plurality of users and the otherindividuals and having links between the nodes representing socialrelationships.

This aspect of the invention takes advantage of the fact thatindividuals or entities in a traditional social network can infer theoverall structure of the traditional network in the individual's orentity's neighborhood and cognizant network (perhaps by manyobservations), and thus the individuals or entities in essence own theirview of the graph structure and its appurtenant content (such as photos,comments, multi-media, texts, and video, subject to digital rightsmanagement, copyright, and privacy restrictions). These views of graphstructure and content, to which the individual or entity has a legalright and technical ability to obtain, can be aggregated, in accordancewith this aspect of the invention, to infer the graph structure of thetraditional social network. Thus, this inference process can be eithercooperative or non-cooperative with respect to the traditional socialnetwork providers. The inferred social network resulting from thisprocess can be implemented independently of the traditional socialnetwork and function as its own social network. In certain embodimentsthe inferred social network and its appurtenant content is stored andimplemented as a distributed peer-to-peer social network, and in otherembodiments it is stored and implemented on a central server, or on ahybrid centralized and distributed network.

Further, cryptographic techniques (such as those set forth in Sections3.6 and 3.7 of Bruce Schneier, Applied Cryptography, John Wiley & Sons,1996, which are hereby incorporated herein by reference) can be appliedto secure the interparty communications within the inferred socialnetwork, with secrets that can be decrypted only in concert with N otherparties. So, shared content within the inferred social network (whetherimplemented with centralized server architecture or peer-to-peerarchitecture) can be kept private, away from any traditional socialnetwork provider. Consequently, privacy is no longer dependent on thestated objectives of a corporation that implements a traditional socialnetwork; rather, privacy is ensured by the storage mechanism itself ofthe inferred social network provided by the invention. For example,although traditional social networks have stated privacy policies, amember of a traditional social network could, for example, copy aprofile page from the traditional social network and e-mail it someone.The privacy ensurance mechanism provided by this embodiment of theinvention, in contrast, cryptographically ensures privacy by the storagemechanism itself, thereby preventing the kind of copying describedabove. This cryptographically ensured privacy can be extended to theinferred graph structure itself, such that the inferred graph structureitself can be reconstituted only by decryption in concert with N otherparties.

One objective of inferring the graph structure in accordance with theinvention is to create a portable social network extrinsic to any majorentity (such as corporations that own traditional social networks),thereby allowing the users of the portable social network, individuallyand in aggregate, to own their own copy of a social network. Thepersonally generated social network can have attached content andindividual parameters (such as privacy settings) that supplement theonline experience. The invention allows the individuals in aggregate tocreate a portable social network that could be copied to anothertraditional social network provider if members of the portable socialnetwork agree. So, for example, the portable social network couldmigrate from a first traditional social network to a second one, causingthe first traditional social network to lose comments, conversations,etc., and the second traditional social network to obtain new users andnew posts. Thus, this embodiment of the invention facilitates transferof subnetworks of the social graph of a traditional social network toanother traditional social network.

Thus, the consumer benefits from the increased portability describedabove, and from privacy that is cryptographically enforced rather thanmerely dependent on a stated policy of traditional social networkproviders. The portability and migration capability allow for theconsumer or groups of consumers to transfer from a traditional socialnetwork provider without losing the extensive connections and stateinformation intrinsic to the traditional social network.

The portability and inference infrastructure provided by the inventioncan be supported by direct subscription or could be advertisingsupported. Advertising can be provided by sending queries to the usersand allowing the users to self-target the advertising by responding tothe queries. Alternatively, data can be mined from the inferred digitalsocial network and advertisements can be targeted to users based on themined data. Alternatively, data can be directly mined locally fromindividual client computing devices with which individual userscommunicate with the inferred digital social network, and advertisementscan be directly targeted to the individual client computing devicesbased on the mined data.

In another general aspect, the invention provides a method of operatingan inferred digital social network, in which information isautomatically obtained from a digital social network for a plurality ofusers of the digital social network. The information includes linkinformation between each of the plurality of users and other individualsin the digital social network. The information is aggregated for theplurality of users to form the inferred digital social network,corresponding to a graph having nodes representing the plurality ofusers and the other individuals and having links between the nodesrepresenting social relationships. Each of the plurality of users isenabled to send and receive message information with other ones of theusers, to view profile information of other ones of the users, and toview social contact information of other ones of the users, through theinferred digital social network.

Thus, the inferred social network can, in follow-on actions, operate asits own stand-alone social network, albeit with information garneredfrom the inference process as well. In certain embodiments of theinvention, this feature allows users to operate as a fullyself-sufficient social network between migration periods from oneunderlying traditional social network to another. In other embodiments,the stand-alone inferred social network does not employ portability andis used instead permanently as a stand-alone social network.

In another general aspect, the invention provides a method of operatingan application program spanning a plurality of the digital socialnetworks. State information is obtained automatically from the pluralityof digital social networks through a plurality of respectivecommunication channels, which can be application program interfaces orcovert or subliminal channels. Input is received from at least one userof the application program in response to the state information obtainedfrom the plurality of digital social networks. In response to the inputfrom the user of the application program, other state information isprovided to the plurality of digital social networks that the digitalsocial networks cause to be communicated to users of the digital socialnetworks. This aspect of the invention makes it possible for multipledigital social networks to be spanned by applications such as onlinegames, personal networking applications, gift-sending applications,product promotion applications, applications for identifying who islooking at a user's profile, applications for ranking connections to auser on the digital social networks, mobile messaging applications, andinferred digital social networks of the type provided by other aspectsof the invention as described above.

In certain embodiments the spanning application is a program thatprovides a unified user meta-interface to enable sharing of contentsimultaneously across the plurality of digital social networks. Thisapplication program can enable digital social networking between theplurality of users across the plurality of digital social networks byenabling content sharing between the plurality of digital socialnetworks. The content shared between the plurality of digital socialnetworks can include a message sent from one of the users of one of thedigital social networks to at least another of the users of another oneof the digital social networks.

The details of various embodiments of the invention are set forth in theaccompanying drawings and the description below. Other features andadvantages of the invention will be apparent from the description, thedrawings, and the claims.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system overview diagram of the computational infrastructureof an inferred digital social network system in accordance with theinvention.

FIG. 2 is a diagram of a traditional social network graph and aninferred social network graph produced in accordance with the invention.

FIG. 3 is a graphical diagram of a social network inference process inaccordance with the invention.

FIG. 4 is a graphical diagram of the details of a process foraggregating inferred and directly entered state information in a socialnetwork inference process in accordance with the invention.

FIG. 5 is an image of a network inference opt-in interface portion of aninferred social network browser page produced in accordance with theinvention.

FIG. 6 is an image of a network display portion of an inferred socialnetwork browser page produced in accordance with the invention.

FIG. 7 is a graphical diagram of a process for secured distributedstorage and recombination of shared content in an inferred digitalsocial network system in accordance with the invention.

FIG. 8 is a flowchart diagram of a process in accordance with theinvention for group voting to transfer or migrate an inferred socialnetwork from a traditional social network provider.

FIG. 9 is a graphical diagram of a process in accordance with theinvention for mining data from a digital social network.

FIG. 10 is an image of a user interface for opt-in credentials andsettings, which is a portion of an inferred social network browser pageproduced in accordance with the invention.

FIG. 11 is a graphical diagram of the relationship between amultiple-network-spanning application in accordance with the inventionand multiple digital social networks spanned by themultiple-network-spanning application.

FIG. 12 is a graphical diagram of a process in accordance with theinvention for a multiple-network-spanning application obtaining stateinformation from and providing state information to a digital socialnetwork.

FIG. 13 is an image of a user consent and initiation portion of aninferred social network browser page produced in accordance with theinvention.

FIG. 14 is a system overview diagram of the computational infrastructureof a meta-social-network spanning application accordance with theinvention.

FIG. 15 is a graphical diagram of a process in accordance with theinvention for operation of a multiple-network-spanning application inaccordance with the invention.

FIG. 16 is a graphical diagram of a process in accordance with theinvention for operation of an inferred digital social network as astand-alone social network.

FIG. 17 is an image of a browser page of an application that managesmultiple social networks simultaneously in accordance with theinvention.

DETAILED DESCRIPTION

With reference to FIG. 1, there is shown the computationalinfrastructure of an inferred digital social network system. A group oftraditional social network provider servers 2000, 2010, and 2020 areaccessible to client computers 3001 operated by users of the traditionalsocial networks, intrinsic applications, and direct queries 3002 fromexternal servers 3000 and 3003 (for example, there is a FACEBOOK appthat runs on FACEBOOK itself that allows certain queries). The inferredsocial network according to the invention is aggregated from informationsources in a manner described below, and stored and accessed on inferredsocial network provider servers 3000 and client computers 3001. Inalternative embodiments, the storage and accessing occurs entirely onone of computers 3001. The arrows in the diagram represent networkconnections between the components to which the arrows point. As isdiscussed below, peer-to-peer social networking and centralizedprocessing are conducted with respect to the inferred social networkprovider. The inferred social network can have all of the properties ofa traditional social network, but the social network may be owneddirectly by the individuals participating in this system.

Intrinsic in the establishment of the inferred social network is theability to target market to its members. Members may benefit fromreceipt of advertising, including incentives, coupons, and otherpromotional material, such as digital value, cash, or watermarkedadvertising with digital cash as described in Serena, “Embedding digitalvalues for digital exchange,” U.S. Patent Application Publication No.2009/0076904, which is hereby incorporated herein by reference. Membersmay choose to self-target advertising, and the self-targeting can bebased on the members allowing localized searching of content byproviders of advertising. Privacy can be maintained by allowing localsearches on shared inferred network content, as is described below.Advertisers and marketers may view a group that has inferred their ownsocial network and is now portable as an attractive target for specificads. The group may share demographic aspects that allow them to demandgreater incentives from advertisers. The advertising process willsupport the corporation that purveys the infrastructure for the inferredsocial network, and will provide a revenue stream for the provision oftools within the inferred social network. The infrastructure for thedistributed computation required by the inferred social network, as isdescribed below, provides capability for delivering advertising to theparticipants in the system and allowing individuals to reclaim their ownnetwork and contacts as their own property, in view of the fact that theindividuals are generating the content delivered to the traditionalsocial network. Furthermore, the inferred social network's business canbe the subject of subscription-based pricing.

Thus, the portable inference infrastructure shown in FIG. 1 can besupported by direct subscription or could be advertising supported.Advertisements can be delivered through the browsing mechanisms orapplications on client computers 3001 with which users interact withprivate social network provider servers 2000, 2010, 2020 and inferredsocial network provider server 3000. Advertisements can also bedelivered through interaction with the inferred social network system.For example, third parties could be allowed to mine data from theinferred social network system and deliver advertisements in response,or keyword search information could be sent from the inferred socialnetwork system to the third party. The advertisements can beself-targeted. In other words, a user can opt into advertisements inwhich the user is interested, such as through a third party sending theuser a query and the user responding. Advertisements may also bekey-word directed, or replaced from other objectionable advertisements,for example. The advertising may be served up directly to the clientinfrastructure 3001 based upon local information and data on clientcomputers 3001. In addition, advertising preferences may be set for theinferred social network.

Advertisements are served to client computers 3001 or inferred socialnetwork provider servers 3000 by a targeted advertising server 3003. Inconnection with interactions between targeted advertising server 3003and client computers 3001, targeted advertising servers 3003 may loadcode and advertising on client computers 3001 for local keyword searchnot shared with inferred social network provider servers 3000, thus,allowing users to rest assured that others in the network cannot seeuser-specific advertisements, which would be based solely on thesearches done on the user's own machine 3001. Advertisements are servedlocally at client computers 3001 and usage data is conveyed to targetedadvertising server 3003 from client computers 3001.

Thus, the inferred social network system can allow for advertising,including purveyance of digital value, based on local searches ofkeywords on client computers 3001. The advertising process causesadvertisements to be stored on a user's local machine 3001, based onself-targeting and keyword conveyance based on local searches of thecontent list. Therefore, the central advertisement server need onlycollect conveyance information and need not search conversations in thetypical manner to convey advertisements. The advertisements would beresident on a client machine 3001 and private information could besearched privately and advertisements targeted, while the privateconversation (or other multimedia interaction) need not be stored on acentral server.

FIG. 2 shows diagrams of a traditional social network graph 1000 and aninferred social network graph 1020 produced in accordance with aninference algorithm that takes individual views of traditional socialnetwork graph 1000 and aggregates them into an overall inferred picture1020 of the graph.

In this document a graph G is defined as an ordered pair (V, E) of a setV of vertices or nodes and a set E of edges, which are two-elementsubsets of V. A line graph of an undirected graph G is defined asanother graph L(G) that represents the adjacencies between edges of G.That is to say, any two vertices of L(G) are adjacent if and only iftheir corresponding edges in G share a common endpoint (“are adjacent”).

Users 1, 2, 4, and 5 in FIG. 2 opt in to the inferred social network,and so a graph structure 1020 is inferred based on the information abouttraditional social network 1000 obtained from the observations of users1, 2, 4, and 5. In some instances, user 3 may be inferred from knowledgeof 2 and 4's connections. Traditional social network graph 1000represents the graph structure stored in the traditional social networkprovider's system. Depending on the resolution of a unique login name ofuser 3 (in order to ensure that common names are distinguished from oneanother, as is done by credit agencies) the inferred graph 1020 may showtwo connections to separate nodes from 2 and 4 rather than one node 3connected to both nodes 2 and 4. Until sufficient information isgarnered and the unique login identity of node 3 is ascertained, node 3might not be resolved to a unique user. The inference algorithm usesprofile information and other information garnered from user 1, 2, 4 and5's data sources to resolve the ambiguity concerning user 3.

The algorithmic process for inferring a digital social network isoutlined in FIG. 3. In step 1040, known adjacency links with potentialweightings are obtained with respect to a particular user of one or more“target” traditional digital social networks, as is described in Serena,U.S. patent application Ser. No. 13/177,856, supra. Then, in step 1050,the system for inferring the digital social network merges thisinformation with other views of the adjacency links for the same user aswell as other users, in an iterative process, taking into accountprivacy restrictions of the inferred social network (discussed below).Aggregation logic 1060 is then applied. Aggregation logic 106 usestimestamps of the links, which show the links as of a certain time,since the graphs are constantly changing, to resolve the current view ofthe network or networks. When individual views are aggregated a view ofthe target social network or networks can be inferred that is of higherfidelity, including an ability to see far into the target network ornetworks, compared to the target traditional social network providerdata model from which data is mined. From a real-time computationalstandpoint, the target network or networks have a time rate of change(i.e., additions, modifications, and deletes) and the graph inferencemodel will lag behind the changes in the target network or networks.Eventually, however, the individual views in aggregate will catch up tothe target network or networks for a specific time step. This time lagis a reality that is well known to those skilled in the art of databasedesign. This invention addresses the time lag by capturing additions,modifications, and deletions to individuals' graph structures byallowing corresponding additions, modifications, and deletions to theuser interface (discussed below) of the inferred social network.

Once the aggregation is complete, step 1070 causes each user's locallyaccepted view of the inferred graph to be stored, with admissibleappurtenant digital content (such as digital content consistent withdigital rights management restrictions, or photos legitimately takenfrom an underlying traditional networks based on privacy restrictions orcopyright restrictions). In step 1080, an overview of the entireinferred graph is stored, with privacy protections of the type shown inFIG. 7 (discussed below). If information is stored locally at a clientcomputer, it is encrypted if the operator the local machine is notsupposed to see that information. If information is stored in a centralserver, the central server stores privacy information so the centralserver does not send data to parties who should not obtain it.

FIG. 4 illustrates in detail the aggregation process, discussed inconnection with FIG. 3. This process aggregates inferred information anddirectly entered state information (such as a person being identified asa friend or on a block list, on a private target traditional socialnetwork itself). This information is obtained from a number of sources,including traditional social network login queries 5000 (such asclicking on a friend's page, or a display of a list of friends on atraditional social network), social network targeted advertising logic5010 (such as a keyword search on a traditional social network thatshows that a user is interested in a particular kind of music), andsocial networking intrinsic applications 5020 for querying graph data(such as a FACEBOOK app similar to FARMVILLE, which exposes a wholeapplication program interface to mine the graph structure forinformation relevant to the inference process, instead of having toscreen scrape through a browser as in block 5000). In addition, a databrowser and/or application monitor 5050 monitors, captures content as itis input to, and enters data into, the traditional social network ornetworks, including acquiring graph appurtenant data such as photos,comments, multi-media, texts, and video, all of which can be kept intactduring migration of the inferred social network from one traditionalsocial network to another. In certain embodiments, browser or monitor5050 acts as meta-user interface (discussed below in connection withFIG. 17) for interactions with multiple social networks (which in someembodiments can co-operatively supply information to the inferenceprocess). The information for a particular user is aggregated and storedat block 5010. By iteratively capturing inputs the inferred socialnetwork can be kept more current with respect to the target network andcomments and other user generated content can be captured. Next, thisaggregated information is further aggregated with correspondinginformation for multiple users in block 5020. In other words, afterfirst aggregating a particular user's own information, multiple users'information is aggregated all together, in a process that produces, inblock 5300, merged shared data of the social network, which is conveyedback to an internal model 5150 of the inferred social network. Theresultant information in internal model 5150 is passed to an overalldisplay model (block 5400) for display to users in the manner shown inFIG. 6, discussed below. This display can provide for multi-views of thesocial networks. In other words, given that a user has an internal modelbased on multiple traditional social networks, the user can select toshow subject matter from only a first traditional social network or onlya second traditional social network, or all of subject matter together.The display can also include actual links in the inferred social networkfunctioning as a stand-alone social network, since the inferred socialnetwork is fully functional and can have its own links as well and itsown state information. The social network monitoring and inferencedescribed in connection with FIGS. 3 and 4 can be built into a browser,an application, or an operating system itself.

FIG. 9 illustrates in detail the process of obtaining graph and contentinformation (which is in turn part of the overall social networkinference process disclosed in FIG. 3). In particular, in FIG. 9, graphand content information is obtained from a transaction monitor program9020, which mines for contact information, and for which traditionalsocial network the contacts come from, and for the http/https data thatis being exchanged between a user's browser and a traditional socialnetwork provider (everything that comes up on a user's browser).Transaction monitor program 9020 may be a program, a browser or browserextension, or an intrinsic part of the operating system of the hostplatform.

A user typically interacts from an application 9005, such as a browser,with a traditional social network provider 9000. After a one-time opt-inprocess for each traditional network (shown in FIG. 5, discussed below),a query process 9030, which could log in automatically to thetraditional social network, can directly query transaction traditionalsocial network provider 9000. The queries to traditional social networkprovider 9000 may be in http or https accesses, intrinsic FACEBOOK appsor other traditional social network apps, target ad information queries,or other database query mechanisms. Query process 9030 can also querytransaction monitor application 9020, thereby pulling information from auser's computer such as new information from an OUTLOOK contact list orother contacts list. Query process 9030 can also query targetadvertisement information (see box 5010 in FIG. 4), for example byobtaining the target advertisement information through an applicationprogram interface of traditional social network provider 9000, theapplication program interface being designed for advertising purposesand providing data that the advertisers use to target advertisements.This advertising data can be used to obtain information about the graphand its content. In addition, often browser application 9005 interactswith OUTLOOK or other social network contact management systems 9010.This information leaves residual markers in the host user's socialcontact list database for social network contact management system 9010,such as a FACEBOOK URL, webpage address, or LINKEDIN photos having aLINKEDIN logo on them. Transaction monitor application 9020 queries theintrinsic data of social network contact management system 9010 (such aswhatever data is in a user's OUTLOOK contacts list), and also monitorsthe process of additions, edits, insertions, and deletions into or fromdatabase to garner the user's direct neighbor list. A merge process 9040(which corresponds to blocks 5200-5400 in FIG. 4) accesses data sourcesfrom different users and applies internal inference logic to furthercharacterize the connections of the social network graph. As more andmore people opt in to the inference process a better picture of thesocial network emerges for all users. Aggregated information is morecomprehensive than the individual views of the traditional socialnetwork data.

Not only do transaction monitor application 9020 and query process 9030garner information about the graph structure; the actual multimedia andtext content (such as conversations) is stored privately. Once the graphstructure is known from FIG. 9, this data can be added to theappropriate nodes or links. The information such as multimedia, photos,text, and music content, is placed in a database for retrieval based onthe inferred graph structure of the network. The starting point for userinteraction with the inferred digital social network is shown in FIG.13, which presents the entry point for the inferred social networkfunctionality for a user (who might have been invited into the inferredsocial network by a friend on a traditional social network). The systemallows a user to enter a login name and password in box 12150, and toregister for the inferred social network using register button 12130.Button 12110 allows downloading of supporting applications to facilitateall of the aspects of the inferred social network. Terms of service mustbe agreed to using box 12100, and the terms of service can be accessedusing box 12120. In addition, help with the login initiation process isavailable through system help link 12140. Upon completion of the userconsent and initiation of participation process, the inferred socialnetwork can be accessed with all of the functionality of a traditionalsocial network.

After the user consents to participation in the inferred social network,the user can “opt in” to the inferred network obtaining information frommultiple traditional social networks. FIG. 5 shows an opt-in interfacethat allows the user to opt in to multiple social networks, therebycapturing as much state and graph theoretical link information as isavailable. The opt-in process captures login information so that theuser's automated inference engine can engage in direct queries of eachtraditional social network provider. Column 704 allows for entering oflogin information or editing of same. Column 705 displays some statusinformation about the target network. Columns 701 and 702 displaygraphics and naming of the traditional social network providers. Anopt-in button 703 allows for commencing inference on a particular targettraditional social network.

Once the user as elected to opt in to a traditional social networkthrough the process described above, the user is allowed to setinference methods and privacy settings for the particular traditionalsocial network, through the user interface shown in FIG. 10. Logincredentials are obtained through boxes 10110 for a given traditionalsocial network represented by logo 10100. The user sets the level ofinference by the system with respect to the particular traditionalsocial network using menu 10120, and the user sets privacy settingsassociated with the inference process using menu 10130. The settings arecaptured and saved when the user selects save box 10120, or else thesettings are canceled. The settings for privacy can allow definedsubgraphs of users to join in the inference process, and can set theextent to which the inferred social network results are shared. Menu10130 can also be used to select the types of inference allowed. Forexample, shared information can be constrained to native friends in themanual settings of the inferred social network. Alternatively, privacysettings for the inference process can depend on a particular degree ofseparation such as “friends of friends.” This process restricts thecollaborative setting for the inference process to a specific subgraphor subgroup in a user's inference network. Similarly in menu 10120, theinference model can be selected along with sources of the information:“Direct queries” may be possible with such instruments as intrinsicFACEBOOK or GOOGLE+ apps; “collaborative inference” is the processdescribed herein that allows for groups of people or entities to pooltheir inference capabilities to obtain a more accurate model of atraditional social network's graph structure.

After the user has consented to participation in the inferred socialnetwork (FIG. 13) and “opted in” to the inferred network obtaininginformation from multiple traditional social networks (FIGS. 5 and 10),the user can access an inference network display, an example of which isshown in FIG. 6. FIG. 6 displays a graph isomorphic to graph 1020 ofFIG. 2. The links 605, 606, 614, and 620 represent multi-traditionalsocial network connections (i.e., connections from multiple traditionalsocial networks in the same view) and some native connections for theinferred social network. For example, links 620 and 605 may representLINKEDIN connections in concert with a link for the inferred socialnetwork, and link 614 may be a link that is a FACEBOOK link. Link 606may represent a link that exists solely within the inferred socialnetwork itself. Individual users in the graph are represented by nodes610, 611, 612 and 615. The basic information for the links and nodes isaccessible through the inferred network connections. Individual links inFIG. 6 can be color-coded to indicate the source traditional socialnetwork for the information. The user can click on the nodes and linksto pull up the appurtenant social content and information associatedwith the nodes and links.

After the social network is inferred, additional content can be added tothe interaction. Interactions can take place extrinsic to thetraditional social network providers, and content can be stored andaccessed in a cryptographically secure manner by applying basic “secretsplitting” protocols such as those set forth in the followingreferences: Sections 3.6 and 3.7 of Bruce Schneier, AppliedCryptography, supra; A. Shamir, “How to Share a Secret,” Communicationsof the ACM, v. 24, n. 11, November 1979, pp. 612-13; G. R. Blakley,“Safeguarding Cryptographic Keys,” Proceedings of the National ComputerConference, 1979, American Federation of Information ProcessingSocieties, v. 48, 1979, pp. 313-317; G. J. Simmons, “An Introduction toShared Secret and/or Shared Control Schemes and Their Application,” inContemporary Cryptology: The Science of Information Integrity, G. J.Simmons, ed., IEEE Press, 1992, pp. 441-497; Y. Desmedt and Y. Frankel,“Threshold Cryptosystems,” Advances in Cryptology-CRYPTO '89Proceedings, Springer-Verlag, 1990, pp. 307-315; Y. Desmedt and Y.Frankel, “Shared Generation of Authentication and Signatures,” Advancesin Cryptology-CRYPTO '91 Proceedings, Springer-Verlag, 1992, pp.457-469; I. Ingemarsson and G. J. Simmons, “A Protocol to Set Up SharedSecret Schemes without the Assistance of a Mutually Trusted Party,”Advances in Cryptology-EUROCYRPT '90 Proceedings, Springer-Verlag, 1991,pp. 266-282; P. Feldman, “A Practical Scheme for Non-interactiveVerifiable Secret Sharing,” Proceedings of the 28^(th) Annual Symposiumon the Foundations of Computer Science, 1987, pp. 427-437; T. P.Pederson, “Distributed Provers with Applications to UndeniableSignatures,” Advances in Cryptology-EUROCRYPT '91 Proceedings,Springer-Verlag, 1991, pp. 221-242; A. Beutelspacher, “How to Say ‘No’,”Advances in Cryptology-EUROCRYPT '89 Proceedings, Springer-Verlag, 1990,pp. 491-496; K. M. Martin, “Untrustworthy Participants in Perfect SecretSharing Schemes,” Cryptology and Coding III, M. J. Ganley, ed., Oxford:Clarendon Press, 1993, pp. 255-264. Additional content can be in theform of “relationship pages,” link-quality indications or other shareddigital content, as is described in Serena, U.S. patent application Ser.No. 13/177,856, supra.

FIG. 7 illustrates a process for secured distributed storage andrecombination of shared content, using shared secrets, as is describedin the cryptology references cited above, to divide private sharedcontent between users and then recombine the shared content with thecooperation of a requisite number of users. First the shared content isgenerated in step 700. This content could be a conversation or othermultimedia content. Then the information is divided in step 705. Theshared secrets can be divided by an individual or divided by anotherprotocol without that individual (as described in Sections 3.6 and 3.7of Bruce Schneier, Applied Cryptography, supra) such that the sharedsecret is stored in N encrypted parts 711, 712 and 713. The informationis accessed and recombined in step 720 according to a secret sharingprotocol (by conveying parts 1 through N in an encrypted format; gettingthe other parties to the secret to send their shares, and thenrecombining the parts). The whole private network can work this way. Forexample, 3 of 5 key people may be required to cooperate in order toreconstitute the network. Although not shown in the figure, a write to ashared disk volume (any change in the data) can be treated as newgenerated shared content and stored via the cryptographic protocolinitiated at step 700, or else it won't be protected; in this caseeveryone knows the secret already, but the protocol is implemented tomake it harder for someone else to obtain it. The secret could be thegraph itself, or appurtenant content. The protocol could require onemember, or a requisite number of members to assent in order toreconstitute the information. Private page files of the mounted diskvolume will minimize network traffic in executing the protocol,culminating in display and presentation of the shared content forviewing and processing (step 725) and interaction with a mountable diskvolume such as a shared volume that would be privacy encrypted anddisplayed on a client computer under “my computer” (step 730).

The inferred social network can be constructed in such a manner that itcan be made portable between traditional social network providers. Thisportability allows individuals or groups of individuals to migratebetween traditional providers en mass—possibly to make a politicalstatement. This portability also allows groups of individuals to boycottcertain providers if they do not like their privacy or advertisementdisbursement methodologies for example. Boycott rights have specialstatus in many countries for asserting consumer protections. Forexample, if a parent group wants to move its children off of the majorprovider of the social network they can do so with this portableinferred social network schema. An additional example could be a groupof children on a network maturing at the same time and migrating en massto a traditional social network while preserving their shared content.The portability allows the moving group to control its online experiencewith respect to the social network and ensure that the group's policiesare being adhered to by the traditional provider. The group migrationrationale and rights are often intrinsic to many worldwide legalsystems. The group may use actual migration or the threat of migrationto change onerous legal terms of service or negotiate payments for theintrinsic value of that group's inferred social network.

Migration can be an assertion of intrinsic legal rights of an individualor group and their implicit and explicit rights over their own socialnetwork and connectivity in the host legal system. Countries mayactually adopt laws that are more conducive to the assertion of grouplegal rights of migration across traditional social network providers.These existing rights can support the maintenance of the inferred socialnetwork by individuals and their groups. Certain rights of theindividual and groups transcend any terms of service to aggregate andanalyze the data from their own social contacts. For example, atraditional social network typically restricts what can be done on thenetwork, but the private network of the invention is not so restricted.While these rights of individuals and groups are host-country specific,generally it is acknowledged that ownership of one's social contacts isone's own right in concert with one's social network's acquiescence Inother words, if other people acquiesce to participating in anindividual's social network, then an individual has the right to whatthey agree to. Distributed peer-to-peer functionality and storage ofinformation can be employed, with no central server, thereby ensuringagainst inappropriate restriction by governments hostile to freedom ofspeech and association.

Voting by formed subgroups of an individual (all the people who haveopted into an individual's or subgroup's private network) can beconducted once an inferred social network has been established.Subgroups of the network can vote to extricate themselves from onerousterms of service that do not sufficiently respect privacy rights,protection of minors, or free expression, for example. These terms ofservice can be renegotiated by threatening transfer of one's group toanother social network. This kind of action has been largely precludeddue the complexity of maintaining ones interconnections across multipletraditional social networks. The present invention facilitates suchtransfers, while maintaining privacy of the social network graph in anopen format that enforces privacy through cryptological techniques andconducts agreement/voting protocols for group decision-making. Wheneverpeople aggregate information, there are consequences to other people,such as their privacy, and cryptological techniques provide a mechanismfor protecting privacy.

FIG. 8 demonstrates how a group, formed at step 801, can choose tomigrate from a social network provider. A cryptographic voting protocolcan be applied (step 802) to initiate the migration process from atraditional social network. The result of the voting process yields adecision at step 805. If the decision is no, the social graph status quois maintained (step 807). If the decision to migrate is yes, the groupmigrates to a designated social network provider. This invention allowsfor a bidding process (step 815) from the destination traditional socialnetworks where they bid with resources and terms of service for themigrating group. Each bid is evaluated (step 855), and a decision ismade with respect to each bid, iteratively whether to migrate to the newsocial network (step 850). If the decision is no, another bid isevaluated, or, if there are no more bids, the social graph status quo ismaintained (step 860). If the decision to migrate is yes, the groupmigrates with all of the content of the inferred social network to thedesignated social network provider (step 810), and the process iscomplete (block 820). Ultimately, the group transfers to the mostfavorable conditions for the group (the group votes collectively towhich network it likes best, and the group migrates into the winningbidder).

The private social network framework described above can support typesof shared content that are meta-traditional-social-network. Inparticular, there can be games (see FIG. 11) that span a number ofsocial networks. The games can be designed to engage participants acrossseveral social networks simultaneously. The system can cooperativelyplay games and share content across multiple social networkssimultaneously. Other games could pit groups from one social networkagainst another for “tug-of-war” games based on relative strengths oftheir social connections. In general, a plug-in application frameworkfor the inferred social network can be provided to allow not only gamesbut general applications that work in the inferred social networkframework. The apps can be such things as contact management tools tomanage contact migration from one traditional social network to another.For example, a particular user could have a friend on LINKEDIN that hethinks would be better suited to a connection on FACEBOOK. The appfacilitates management of contact migration across social networks. Theuser's friend could be added to FACEBOOK and delete from LINKEDIN. Theinferred social network maintains all contacts and the network model.Also, relationship networks as described in Serena, U.S. patentapplication Ser. No. 13/177,856, supra, can span a number of traditionalsocial networks while being supported by the private social networkframework described above. Other types of applications that can besupported by the inferred social network include applications formarketing, barter, auction, or exchange of digital value, applicationsfor suggesting friends or reaching individuals who are not yetparticipants of social networks.

Thus, the inferred social network supports content extrinsic totraditional social network providers, thereby enhancing the traditionalsocial network experience. The inferred social network also supportsconcurrent management of multiple traditional social networks, such as,at a minimum, supporting simultaneous conversations across multiplenetworks and supporting content sharing between platforms. In, additionprivacy settings and digital rights management can be set acrossmultiple platforms.

The inferred social network as a stand-alone network will have profileinformation about the user. That profile information can be added to ordeleted from the managed traditional social networks or vested only inthe inferred social network. For example, resume information may beposted to LINKEDIN by the inferred social network; however FACEBOOK andGOOGLE+ would not obtain that information.

The inferred social network can be stored either as a distributedsystem, central server, peer-to-peer system, or hybrid (for example, thepeer-to-peer functionality of the inferred social network can besupplemented with centralized servers for ease of computation in earlyinstantiations of network). The specific details of the network storagemethod and retrieval can be abstracted away though standard data queriesthat hide the concurrent and distributed logic from applicationprogramming interfaces with which the inferred social network interacts.Once the abstracted data structure adequately addresses concurrency,versioning, and shared accesses, the system allows for the standardqueries of the traditional social network and advanced queries of theinferred, private social network. The advanced queries allow forspanning multiple social networks and managing interactions acrossnetworks. Furthermore, the profile can be searched to obtain friendswith shared interests (based on profile information) and to managefriendship placement in and removal from the appropriate traditionalsocial network.

As was mentioned above, the inferred social network can operate as afunctional traditional social network, as is shown in FIG. 16. First theinference process defines and aggregates information to form the network(step 16000). Then, in an iterative process, the network is used as afunctional social network (step 16010). The functionality that isprovided by traditional social networks such as GOOGLE+ and FACEBOOK cannow be executed. Illustrated in the figure are some elements of thefunctionality; however, basic functionality as is known to those skilledin the art may be incorporated. For example the inferred social networkallows its users to send and receive messages (step 16020). Further,content can be shared such as photos or video (step 16030). Both profileand contact information can now be viewed (steps 16040 and 16050). Theinferred social network described above is one example of an applicationthat spans multiple traditional social networks and supportsapplications, such as games, that also span the multiple traditionalsocial networks. A similar framework can support other types of“spanning” applications, entirely distinct from inferred socialnetworks.

FIG. 11 illustrates, generally, a spanning application 11140 that iscapable of spanning multiple social networks 11100, 11110, 11120, and11130 simultaneously or sequentially. The principal concept is a unifiedexecution structure whereby an application 11140 can span multiplesocial networks 11100, 11110, 11120, and 11130. That is to say,application 11140 automatically obtains state information form socialnetworks 11100, 11110, 11120, and 11130, receives input from a user inresponse to the state information, and in response to the input from theuser, provides other state information to social networks 11100, 11110,11120, and 11130 that the social networks communicate to their users,The application 11140 may actually execute using native APIs of thetraditional social networks, or application 11140 can communicateinformation through sockets, http, remote procedure calls, or othermethods known to those skilled in the art for application communication,including covert or subliminal channels (described below) if nativeapplication programming interfaces of the social networks do not allowsufficient interaction of the spanning application with the socialnetworks. The system can be implemented such that code for the spanningapplications executes on one or more client computers 3001 in FIG. 1 orany of the other computational systems shown in FIG. 1 or FIG. 14. Thecommunication techniques can yield the ability to conditionally transmitdata to another social network, inclusive of the inferred socialnetwork, through a variety of communication methods. The spanningapplication in one embodiment can run on an inferred social networkprovider 3000 or an advertising provider 3003 shown in FIG. 1, or on asocial network provider 13000, 13010, 13020 or a social network client13040 or a spanning application support server 13030 shown in FIG. 14,to interact with the multiple social networks. The spanning applicationcan be implemented in a number of ways using standard distributedcomputation methods or standard client-server models of computation. Thepresentation of the application information similarly can take knownforms as the user interface design allows. In certain embodiments, thespanning application accesses the APIs of traditional social networkproviders and the API for an inferred social network provider if it ispresent. Digital information appurtenant to the graph structure of thenetwork (such as photos, comments, multi-media, texts, and video) isavailable at the inferred social network, and similarly the spanningapplication can collect or infer information and viably disseminate itto other spanning applications. The availability of the APIs for socialnetwork providers that access the graph structure allow for the creatingof spanning applications that access all of the APIs of all of thesocial networks concurrently and that compute across all the socialnetworks available. This technique enables the user of the spanningapplication to be presented with a seamless appearance of the userinterface across the multiple social networks

FIG. 12 illustrates how a social network spanning application describedin FIG. 11 accesses the intrinsic API of a native social networkingplatform (block 12001). There are standard communication mechanisms(block 12002) available to the native APIs of the social network. Inaddition, there are nonstandard typical modalities of communication nottypically allowed in the social network API such as sockets and remoteprocedure calls. From given allowed communication accesses in a nativesocial networking application, the nonstandard modalities can beconstructed, thereby expanding the capabilities of the available API forthe spanning applications. These communication mechanisms allowcommunication between the native social networking platform and thespanning application or social networking server infrastructure 12003,to allow the spanning application to execute across multiple socialnetworking systems. As was previously stated, the server infrastructurecan be distributed (peer-to-peer) or centralized in design.

FIG. 14 illustrates the computational infrastructure for a socialnetwork spanning application. Multiple social network providers 13000,13010, and 13020 each have their own computer infrastructure. APIs maybe available for access by the spanning application. Spanningapplications can run on social network clients 13040, social networkproviders 13000, 13010, and 13020, or spanning application supportserver infrastructure 13030. The components of the computationalinfrastructure communicate over a TCP/IP internet system represented byarrows in the figure. Communication can be direct when provided byintrinsic APIs of the subsystems, or when there is insufficient support,covert or subliminal channels can be constructed to allow communicationbetween constituent spanning application subsystems.

In particular, social network providers 13000, 13010, and 13020 may ormay not provide an API for accessing their information and designingapplications that are resident on their network. The API may be ofsufficient maturity to allow for standard communication mechanisms. Inthe absence of direct API procedure calls for communications, however,it is possible to convey information through covert or subliminalchannels. The literature known to those skilled in the art providesexample methods whereby accessing information such as web links canconvey binary values. Once binary values have been conveyed, standardcommunication mechanisms may be constructed out of the covert channel. Acovert channel can be used to write from a read-only API, such as bytoggling between multiple read accesses, as is known in the art, and ontop of the covert channel it is possible to build communicationconstructs such as sockets, remote procedure calls, or othercommunication mechanisms. This practice allows the traditional socialnetwork intrinsic API to be expanded to convey additional information.This information will be used as input to the social network spanningapplication as it performs standard execution on its appurtenant hostplatforms. FIG. 15 depicts the general operation of a social networkspanning application. The application is capable of gathering input dataand interacting with the social networks through multiple APIsappurtenant to the social networks (block 15000). The application alsoobtains user input into the spanning application (block 15010). Theinformation is aggregated and the application can run and communicatewith multiple social networks through clients, servers and socialnetwork APIs (block 15020). If the intrinsic API of the social networkdoes not support communication with the server or client infrastructure,a covert channel known to those skilled in the art may be used for thispurpose. The social networks accessed by the spanning application canconditionally include an inferred social network of the type describedabove. An example application could be a game, (such as FARMVILLE or anysimilar social-network-based game), in which players are obtained frommultiple social networks. The game communicates messages about the stateof the game back to the multiple social network APIs (block 15020) aftercomputing what changes in state information have occurred. The game canbe played across all social networks simultaneously. Yet another exampleis a spanning application that serves up shared content that isaccessible to selected users but stored extrinsically to any one socialnetwork, the shared content including items such as photos orconversations, including private photos that only friends share and notheld on any one social network. Other examples or spanning applicationsinclude: opt-in advertising applications for multiple social networks;personal networking applications, such as business networkingapplications; gift sending applications; product promotion applications;search Engine promotion applications; applications for identifying,across multiple social networks, who is looking at a user's profile;birthday greeting applications for multiple social networks;applications for ranking connections to a user on multiple socialnetworks; mobile messaging and SMS applications; applications forpublishing blogs, media, and other material to multiple social networks;applications for customer interaction on multiple social networks,including targeted advertising applications and customer feedbackapplications; e-mail list management applications; polling applications;coupon applications; contest applications; appointment schedulingapplications; shopping cart applications; and, many other types ofapplications.

Another example of a spanning application is an application that ensuresconsistent messaging and conversation state across multiple socialnetworks. As is shown in FIG. 17, such an application manages multiplesocial networks simultaneously and functions as a meta-interface to themultiple social networks. With the meta-social networking systemmanagement interface one can obtain cognizance of content andconversations across multiple social networks. An inferred socialnetwork may or may not be included as one of the social networks spannedby the spanning application, and in general this spanning applicationmay either be supported by an inferred social network architecture ofthe type described above or it may operate wholly independently of anyinferred social network architecture. The meta-interface and managementsystem allows for maintenance of private content (e.g., photos, music,video, and other media represented by icons 156 or, in other examples,the conversation as a whole). Conversations and interactions betweenusers can span multiple social networks, shown in network interfaces 152and 160. The meta-interface displays responses to content shared betweennetworks and maintains the conversation state across themeta-social-networking construct. For example, Alice broadcasts on allnetworks that she saw a great video (comment 154). Bob responds only ontraditional social network 1 that he enjoyed the video to 155 and postscontent (possibly private as described herein) to a shared contextextrinsic to all of the traditional networks (media represented by icons156). Eve and Stewart respond on their respective traditional socialnetworks 1 and 2 (comments 157). And finally, in the conversation Aliceand Bob post (not necessarily in tandem) a comment to all networks,possibly inclusive of the inferred network (comment 158). Interfaces 152and 160 represent user interface elements to the underlying socialnetworks to enable the user to manage the multiple social networkssimultaneously from one meta-social networking program. The multiplesocial network interfaces may be a graph such as is shown in FIG. 6,albeit links and nodes may be colored with which social network eachlink or node originated from. This interface shown in FIG. 17 isillustrative and may take other user interface forms known to thoseskilled in the art of user interface design and social networkingprogramming. Privacy settings and Digital Rights Management for theconversation elucidated in FIG. 17 may be applied by the user or theowner of the content shared. In FIG. 17, the user sends messages fromone social network to another user that may be confined to only onesocial network. For example, in comments 157, Stewart may only belong totraditional social network 2 and Eve may only choose to belong totraditional social network 1. Standard messaging protocols know to thoseskilled in the art will be applied to facilitate transmission acrossmultiple social networks.

A system has been described whereby individuals can take back ownershipof their own social network information by collaboration technically andpolitically to obtain a picture of the network: “the inferred socialnetwork.” This view of the network is distributed, time-stamped, andversioned so that collaborating individuals can use it as one does atraditional social network with additional functionality as enumeratedherein. Advertising and incentives derived from the inferred socialnetwork can be purveyed to users and remuneration can be meted out tothe appropriate parties. Furthermore, privacy is no longer just a statedproperty of shared online content; it is protected by knowncryptographic protocols and techniques such as those described in thecryptology references cited above. The flow of data in this system canbe distributed in such a manner that individuals “own their own” socialnetwork and establish connections via inference and behavior as atraditional social network does. In essence, the individuals own theirown picture of the social network both legally and technically.Applications can be developed that span multiple social networks, bothtraditional and inferred social networks. Such spanning applications canbe supported by the inferred social network or can functionindependently of an inferred social network. The inferred social networkinfrastructure can be supported by all forms of advertising or directsubscription. While nothing herein should preclude the operation of theinferred social network as a traditional social network, the inventionis not just social network analysis; it is social network analysis toestablish a useable inferred social network or equivalentlymeta-social-network interface with added features, as well as spanningapplications that work across multiple social networks.

While several particular forms of the invention have been illustratedand described, it will be apparent that various modifications andcombinations of the invention detailed in the text and drawings can bemade without departing from the spirit and scope of the invention. Also,references to specific flowchart steps or specific browser pages and theelements thereof are also not intended to be limiting in any manner andother steps and elements could be substituted while remaining within thespirit and scope of the invention. Accordingly, it is not intended thatthe invention be limited, except as by the appended claims.

1. A method of operating an inferred digital social network, comprisingthe steps of: obtaining consent from a plurality of users of at leastone digital social network to participation in an inferred digitalsocial network, automatically obtaining information from the at leastone digital social network for the plurality of users of the at leastone digital social network, the information including link informationbetween each of the plurality of users and other individuals in the atleast one digital social network, and aggregating the information forthe plurality of users to form an inferred digital social networkcorresponding to a graph having nodes representing the plurality ofusers and the other individuals and having links between the nodesrepresenting social relationships.
 2. The method of claim 1, furthercomprising copying the inferred digital social network to at least oneother digital social network so that the graph is incorporated into theat least one other digital social network.
 3. The method of claim 2,further comprising receiving votes from the plurality of users tomigrate the inferred digital social network to the at least one otherdigital social network, and wherein the step of copying the inferreddigital social network to the at least one other digital social networkis based on a requisite number of votes being received.
 4. The method ofclaim 1, further comprising dividing a digital representation of thegraph based on a secret sharing protocol, obtaining assent from at leasta threshold number of the plurality of users, and recombining thedigital representation of the graph based on the obtained assent.
 5. Themethod of claim 1, further comprising enabling digital social networkingbetween the plurality of users within the inferred digital socialnetwork, apart from the at least one digital social network from whichthe inferred digital social network is formed, by enabling sharedcontent within the inferred digital social network between the pluralityof users.
 6. The method of claim 5, further comprising storing theshared content in a distributed manner.
 7. The method of claim 6,wherein the shared content is stored in a peer-to-peer manner.
 8. Themethod of claim 5, further comprising dividing the shared content basedon a secret sharing protocol, obtaining assent from at least some of theplurality of users, and recombining the shared content based on theassent.
 9. The method of claim 5, wherein the shared content is amessage sent from one of the users to another of the users.
 10. Themethod of claim 5, further comprising copying the shared content to theat least one digital social network.
 11. The method of claim 1 whereinthe step of automatically obtaining information from the at least onedigital social network comprises accessing a native applicationprogramming interface for the at least one digital social network andobtaining the information through the application programming interface.12. The method of claim 11, wherein the step of accessing the nativeapplication programming interface is performed through an app of the atleast one digital social network.
 13. The method of claim 11 furthercomprising copying information from the inferred digital social networkto the at least one digital social network through the applicationprogramming interface.
 14. The method of claim 1 wherein the step ofautomatically obtaining information from the at least one digital socialnetwork comprises obtaining the information through a covert orsubliminal channel.
 15. The method of claim 1 wherein the step ofautomatically obtaining information from the at least one digital socialnetwork comprises employing a browser that functions as a meta-userinterface to a plurality of digital social networks.
 16. The method ofclaim 1, wherein there are a plurality of the digital social networks,spanned by the inferred digital social network, from which theinformation is obtained, and the method further comprises copying atleast some of the aggregated information to at least one of the digitalsocial networks spanned by the inferred digital social network.
 17. Themethod of claim 1, wherein there are a plurality of the digital socialnetworks, spanned by the inferred digital social network, from which theinformation is obtained, and the method further comprises: enablingdigital social networking between the plurality of users within theinferred digital social network by enabling shared content within theinferred digital social network between the plurality of users; andcopying at least some of the shared content to at least one of thedigital social networks spanned by the inferred digital social network.18. The method of claim 1, wherein there are a plurality of the digitalsocial networks, spanned by the inferred digital social network, andwherein the method further comprises enabling each of the plurality ofusers to opt in to individual ones of the digital social networks topermit information to be obtained automatically from therefrom.
 19. Themethod of claim 1, further comprising enabling the users to set a levelof inference for the information to be obtained automatically from thedigital social network
 20. The method of claim 1, further comprisingenabling the users to set privacy settings for the information to beobtained automatically from the digital social network.
 21. The methodof claim 1, wherein the other individuals include individuals distinctfrom the plurality of users.
 22. The method of claim 1, furthercomprising storing the inferred digital social network in a distributedmanner.
 23. The method of claim 22, wherein the shared content is storedin a peer-to-peer manner.
 24. The method of claim 1, wherein the stepsof automatically obtaining information from the at least one digitalsocial network and aggregating the information are iteratively repeatedto capture additions, modifications, and deletions in the at least onedigital social network and to reflect the additions, modifications, anddeletions in the inferred digital social network.
 25. The method ofclaim 1 further comprising providing advertising through the inferreddigital social network to the plurality of users.
 26. The method ofclaim 25 wherein the step of providing advertising comprises sendingqueries to the users and allowing the users to self-target theadvertising by responding to the queries.
 27. The method of claim 25wherein the step of providing advertising comprises mining data from theinferred digital social network and targeting advertisements to usersbased on the mined data.
 28. The method of claim 25 wherein the step ofproviding advertising comprises directly mining data locally fromindividual client computing devices with which individual userscommunicate with the inferred digital social network, and directlytargeting advertisements to the individual client computing devicesbased on the mined data.
 29. The method of claim 1, wherein there are aplurality of the digital social networks, spanned by the inferreddigital social network, and wherein the method further comprisesemploying the inferred digital social network to enable digital socialnetworking between the plurality of users across the plurality ofdigital social networks by enabling content sharing simultaneouslyacross the plurality of digital social networks.
 30. The method of claim29 wherein the content shared between the plurality of digital socialnetworks comprises a message sent from one of the users of one of thedigital social networks to at least another of the users of another oneof the digital social networks.
 31. The method of claim 1, wherein thereare a plurality of the digital social networks, spanned by the inferreddigital social network, and wherein the method further comprisesemploying the inferred digital social network to enable individual onesof the users to set privacy settings across the plurality of digitalsocial networks.
 32. The method of claim 1, wherein there are aplurality of the digital social networks, spanned by the inferreddigital social network, and wherein the method further comprisesemploying the inferred digital social network to enable individual onesof the users to set digital rights management across the plurality ofdigital social networks.
 33. The method of claim 1, wherein there are aplurality of the digital social networks, spanned by the inferreddigital social network, the method further comprising: automaticallyobtaining state information from the plurality of digital socialnetworks through a plurality of respective communication channels,receiving input from at least one user of an application program inresponse to the state information obtained from the plurality of digitalsocial networks, and in response to the input from the user of theapplication program, providing to the plurality of digital socialnetworks other state information that the digital social networks causeto be communicated to users of the digital social networks.
 34. A methodof operating an inferred digital social network, comprising the stepsof: automatically obtaining information from at least one digital socialnetwork for a plurality of users of the at least one digital socialnetwork, the information including link information between each of theplurality of users and other individuals in the at least one digitalsocial network, aggregating the information for the plurality of usersto form an inferred digital social network corresponding to a graphhaving nodes representing the plurality of users and the otherindividuals and having links between the nodes representing socialrelationships, and enabling each of the plurality of users to send andreceive message information with other ones of the users, to viewprofile information of other ones of the users, and to view socialcontact information of other ones of the users, through the inferreddigital social network.
 35. A method of operating an application programspanning a plurality of the digital social networks, comprising thesteps of: automatically obtaining state information from the pluralityof digital social networks through a plurality of respectivecommunication channels, receiving input from at least one user of theapplication program in response to the state information obtained fromthe plurality of digital social networks, and in response to the inputfrom the user of the application program, providing to the plurality ofdigital social networks other state information that the digital socialnetworks cause to be communicated to users of the digital socialnetworks.
 36. The method of claim 35 wherein at least some of thecommunication channels comprise application program interfaces.
 37. Themethod of claim 35 wherein at least some of the communication channelscomprise covert or subliminal channels.
 38. The method of claim 35wherein the application program is an online game.
 39. The method ofclaim 35 wherein: the application program is an inferred digital socialnetwork, the state information includes link information in each of theplurality of digital social networks between each of a plurality ofusers of the digital social networks and other individuals in theplurality of digital social networks, and the application programaggregates the state information for the plurality of users to form theinferred digital social network, the inferred digital social networkcorresponding to a graph having nodes representing the plurality ofusers and the other individuals and having links between the nodesrepresenting social relationships.
 40. The method of claim 35, whereinthe application program is a program that provides a unified usermeta-interface to enable sharing of content simultaneously across theplurality of digital social networks.
 41. The method of claim 40,wherein the application program enables digital social networkingbetween the plurality of users across the plurality of digital socialnetworks by enabling content sharing between the plurality of digitalsocial networks.
 42. The method of claim 41 wherein the content sharedbetween the plurality of digital social networks comprises a messagesent from one of the users of one of the digital social networks to atleast another of the users of another one of the digital socialnetworks.
 43. The method of claim 35, wherein the application program isa program for providing, to the plurality of digital social networks,shared content between users of the digital social networks, such thatthe shared content is accessible to the plurality of digital socialnetworks yet stored externally to the plurality of digital socialnetworks.
 44. The method of claim 35 wherein the application program isa program that provides advertising to the plurality of digital socialnetworks, and the input from the user is an opt-in to the advertisingapplication.
 45. The method of claim 35 wherein the application programis a personal networking application.
 46. The method of claim 35 whereinthe application program is a program that promotes a product.
 47. Themethod of claim 35 wherein the application program is a program forranking connections to the user on the plurality of digital socialnetworks.
 48. The method of claim 35 wherein the application program isa mobile messaging application.